Medicine and Statistics Don’t Mix

Some friends of mine recently were trying to get pregnant with the help of a fertility treatment. At great financial expense, not to mention pain and inconvenience, six eggs were removed and fertilized. These six embryos were then subjected to Pre-Implantation Genetic Diagnosis (P.G.D.), a process which cost $5,000 all by itself.

The results that came back from the P.G.D. were disastrous.

Four of the embryos were determined to be completely non-viable. The other two embryos were missing critical genes/D.N.A. sequences which suggested that implantation would lead either to spontaneous abortion or to a baby with terrible birth defects.

The only silver lining on this terrible result is that the latter test had a false positive rate of 10 percent, meaning that there was a one-in-ten chance that one of those two embryos might be viable.

So the lab ran the test again. Once again the results came back that the critical D.N.A. sequences were missing. The lab told my friends that failing the test twice left only a 1 in 100 chance that each of the two embryos were viable.

My friends — either because they are optimists, fools, or perhaps know a lot more about statistics than the people running the tests — decided to go ahead and spend a whole lot more money to have these almost certainly worthless embryos implanted nonetheless.

Nine months later, I am happy to report that they have a beautiful, perfectly healthy set of twins.

The odds against this happening, according to the lab, were 10,000 to 1.

So what happened? Was it a miracle? I suspect not. Without knowing anything about the test, my guess is that the test results are positively correlated, certainly when doing the test twice on the same embryo, but probably across embryos from the same batch as well.

But, the doctors interpreted the test outcomes as if they were uncorrelated, which led them to be far too pessimistic. The right odds might be as high as 1 in 10, or maybe something like 1 in 30. (Or maybe the whole test is just nonsense and the odds were 90 percent!)

Anyway, this is just the latest example of why I never trust statistics I get from people in the field of medicine, ever.

My favorite story concerns my son Nicholas:

Relatively early on in the pregnancy we had an ultrasound. The technician said that although it was very early, he thought he could predict whether it would be a boy or a girl, if we wanted to know. We said, “Yes, absolutely we want to know.” He told us he thought it would be a boy, although he couldn’t be certain.

“How sure are you?” I asked

“I’m about 50-50,” he replied.